Stress-testing remote model querying APIs for relational and graph-based stores

Abstract

Recent research in scalable model-driven engineering now allows very large models to be stored and queried. Due to their size, rather than transferring such models over the network in their entirety, it is typically more efficient to access them remotely using networked services (e.g. model repositories, model indexes). Little attention has been paid so far to the nature of these services, and whether they remain responsive with an increasing number of concurrent clients. This paper extends a previous empirical study on the impact of certain key decisions on the scalability of concurrent model queries on two domains, using an Eclipse Connected Data Objects model repository, four configurations of the Hawk model index and a Neo4j-based configuration of the NeoEMF model store. The study evaluates the impact of the network protocol, the API design, the caching layer, the query language and the type of database and analyses the reasons for their varying levels of performance. The design of the API was shown to make a bigger difference compared to the network protocol (HTTP/TCP) used. Where available, the query-specific indexed and derived attributes in Hawk outperformed the comprehensive generic caching in CDO. Finally, the results illustrate the still ongoing evolution of graph databases: two tools using different versions of the same backend had very different performance, with one slower than CDO and the other faster than it.

Scaling-up domain-specific modelling languages through modularity services

“…units. To improve efficiency, constraints can define a scope and be validated incrementally, while attributes and references can be indexed for more efficient queries [14].…”

“…This describes the different modularization services as patterns which are instantiated on top of the DSML meta-model, and from which a scalable modelling environment with the defined services is synthesized. To improve efficiency, the generated environment makes use of Hawk [14], a model indexer supporting efficient querying across fragmented resources.…”

Non-human Modelers: Challenges and Roadmap for Reusable Self-explanation

“…The server version of Hawk exposes its capabilities through a web service API implemented through Apache Thrift. Prior studies have evaluated how a single Hawk server can scale with an increasing number of clients [7], with competitive or better results than other alternatives (CDO and Mogwai).…”

Guest editorial to the special section on ECMFA and ICMT at STAF 2016

“…-A local and global tour on MOMoT [1], based on ICMT, -Model clone detection for rule-based model transformation languages [4], based on ICMT, -Stress-testing remote model querying APIs for relational and graph-based stores [2], based on ECMFA, -An example is worth a thousand words: Creating graphical modeling environments by example [3], based on ECMFA.…”

“…The work on remote model querying [2] focuses on the storage and access technology for models. With models becoming very large, local access becomes both costly (it is too slow to copy entire models) and impractical (many designers need simultaneous access to large models).…”